{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,3,27]],"date-time":"2026-03-27T20:58:40Z","timestamp":1774645120395,"version":"3.50.1"},"reference-count":44,"publisher":"Oxford University Press (OUP)","issue":"10","license":[{"start":{"date-parts":[[2022,4,12]],"date-time":"2022-04-12T00:00:00Z","timestamp":1649721600000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/creativecommons.org\/licenses\/by-nc\/4.0\/"}],"funder":[{"name":"KAUST Office of Sponsored Research","award":["BAS\/1\/1624-01"],"award-info":[{"award-number":["BAS\/1\/1624-01"]}]},{"name":"KAUST Office of Sponsored Research","award":["FCC\/1\/1976-23-01"],"award-info":[{"award-number":["FCC\/1\/1976-23-01"]}]},{"name":"KAUST Office of Sponsored Research","award":["FCC\/1\/1976-26-01"],"award-info":[{"award-number":["FCC\/1\/1976-26-01"]}]},{"name":"KAUST Office of Sponsored Research","award":["REI\/1\/0018-01-01"],"award-info":[{"award-number":["REI\/1\/0018-01-01"]}]},{"name":"KAUST Office of Sponsored Research","award":["REI\/1\/4216-01-01"],"award-info":[{"award-number":["REI\/1\/4216-01-01"]}]},{"name":"KAUST Office of Sponsored Research","award":["REI\/1\/4437-01-01"],"award-info":[{"award-number":["REI\/1\/4437-01-01"]}]},{"name":"KAUST Office of Sponsored Research","award":["REI\/1\/4473-01-01"],"award-info":[{"award-number":["REI\/1\/4473-01-01"]}]},{"name":"KAUST Office of Sponsored Research","award":["URF\/1\/4098-01-01"],"award-info":[{"award-number":["URF\/1\/4098-01-01"]}]},{"name":"KAUST Office of Sponsored Research","award":["REI\/1\/4742-01-01"],"award-info":[{"award-number":["REI\/1\/4742-01-01"]}]}],"content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":[],"published-print":{"date-parts":[[2022,5,13]]},"abstract":"<jats:title>Abstract<\/jats:title>\n                  <jats:sec>\n                    <jats:title>Motivation<\/jats:title>\n                    <jats:p>Recombination is one of the essential genetic processes for sexually reproducing organisms, which can happen more frequently in some regions, called recombination hotspots. Although several factors, such as PRDM9 binding motifs, are known to be related to the hotspots, their contributions to the recombination hotspots have not been quantified, and other determinants are yet to be elucidated. Here, we propose a computational method, RHSNet, based on deep learning and signal processing, to identify and quantify the hotspot determinants in a purely data-driven manner, utilizing datasets from various studies, populations, sexes and species.<\/jats:p>\n                  <\/jats:sec>\n                  <jats:sec>\n                    <jats:title>Results<\/jats:title>\n                    <jats:p>RHSNet can significantly outperform other sequence-based methods on multiple datasets across different species, sexes and studies. In addition to being able to identify hotspot regions and the well-known determinants accurately, more importantly, RHSNet can quantify the determinants that contribute significantly to the recombination hotspot formation in the relation between PRDM9 binding motif, histone modification and GC content. Further cross-sex, cross-population and cross-species studies suggest that the proposed method has the generalization power and potential to identify and quantify the evolutionary determinant motifs.<\/jats:p>\n                  <\/jats:sec>\n                  <jats:sec>\n                    <jats:title>Availability and implementation<\/jats:title>\n                    <jats:p>https:\/\/github.com\/frankchen121212\/RHSNet.<\/jats:p>\n                  <\/jats:sec>\n                  <jats:sec>\n                    <jats:title>Supplementary information<\/jats:title>\n                    <jats:p>Supplementary data are available at Bioinformatics online.<\/jats:p>\n                  <\/jats:sec>","DOI":"10.1093\/bioinformatics\/btac234","type":"journal-article","created":{"date-parts":[[2022,4,12]],"date-time":"2022-04-12T09:27:51Z","timestamp":1649755671000},"page":"2683-2691","source":"Crossref","is-referenced-by-count":15,"title":["Deep learning identifies and quantifies recombination hotspot determinants"],"prefix":"10.1093","volume":"38","author":[{"ORCID":"https:\/\/orcid.org\/0000-0002-3664-6722","authenticated-orcid":false,"given":"Yu","family":"Li","sequence":"first","affiliation":[{"name":"Department of Computer Science and Engineering (CSE), The Chinese University of Hong Kong (CUHK), 999077, Hong Kong SAR, China"},{"name":"Computer Science Program, Computer, Electrical and Mathematical Sciences and Engineering (CEMSE) Division, King Abdullah University of Science and Technology (KAUST) , Thuwal 23955-6900, Kingdom of Saudi Arabia"},{"name":"KAUST Computational Bioscience Research Center (CBRC), King Abdullah University of Science and Technology , Thuwal 23955-6900, Kingdom of Saudi Arabia"},{"name":"The CUHK Shenzhen Research Institute , Shenzhen 518057, China"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-2382-2248","authenticated-orcid":false,"given":"Siyuan","family":"Chen","sequence":"additional","affiliation":[{"name":"Computer Science Program, Computer, Electrical and Mathematical Sciences and Engineering (CEMSE) Division, King Abdullah University of Science and Technology (KAUST) , Thuwal 23955-6900, Kingdom of Saudi Arabia"},{"name":"KAUST Computational Bioscience Research Center (CBRC), King Abdullah University of Science and Technology , Thuwal 23955-6900, Kingdom of Saudi Arabia"}]},{"given":"Trisevgeni","family":"Rapakoulia","sequence":"additional","affiliation":[{"name":"Max Planck Institute for Molecular Genetics , Berlin 14195, Germany"}]},{"given":"Hiroyuki","family":"Kuwahara","sequence":"additional","affiliation":[{"name":"Computer Science Program, Computer, Electrical and Mathematical Sciences and Engineering (CEMSE) Division, King Abdullah University of Science and Technology (KAUST) , Thuwal 23955-6900, Kingdom of Saudi Arabia"},{"name":"KAUST Computational Bioscience Research Center (CBRC), King Abdullah University of Science and Technology , Thuwal 23955-6900, Kingdom of Saudi Arabia"}]},{"ORCID":"https:\/\/orcid.org\/0000-0001-5516-9944","authenticated-orcid":false,"given":"Kevin Y","family":"Yip","sequence":"additional","affiliation":[{"name":"Department of Computer Science and Engineering (CSE), The Chinese University of Hong Kong (CUHK), 999077, Hong Kong SAR, China"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-7108-3574","authenticated-orcid":false,"given":"Xin","family":"Gao","sequence":"additional","affiliation":[{"name":"Computer Science Program, Computer, Electrical and Mathematical Sciences and Engineering (CEMSE) Division, King Abdullah University of Science and Technology (KAUST) , Thuwal 23955-6900, Kingdom of Saudi Arabia"},{"name":"KAUST Computational Bioscience Research Center (CBRC), King Abdullah University of Science and Technology , Thuwal 23955-6900, Kingdom of Saudi Arabia"}]}],"member":"286","published-online":{"date-parts":[[2022,4,12]]},"reference":[{"key":"2023020109132691100_btac234-B1","doi-asserted-by":"crossref","first-page":"1790","DOI":"10.1093\/molbev\/msaa038","article-title":"Predicting the landscape of recombination using deep learning","volume":"37","author":"Adrion","year":"2020","journal-title":"Mol. 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